Holistic System Design for Distributed National eHealth Services

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A comprehensive survey on Fog Computing: State-of-the-art and research challenges

Cloud computing with its three key facets (i.e., Infrastructure-as-a-Service, Platform-as-a-Service, and Softwareas- a-Service) and its inherent advantages (e.g., elasticity and scalability) still faces several challenges. The distance between the cloud and the end devices might be an issue for latencysensitive applications such as disaster management and content delivery applications. Service level agreements (SLAs) may also impose processing at locations where the cloud provider does not have data centers. Fog computing is a novel paradigm to address such issues. It enables provisioning resources and services outside the cloud, at the edge of the network, closer to end devices, or eventually, at locations stipulated by SLAs. Fog computing is not a substitute for cloud computing but a powerful complement. It enables processing at the edge while still offering the possibility to interact with the cloud. This paper presents a comprehensive survey on fog computing. It critically reviews the state of the art in the light of a concise set of evaluation criteria. We cover both the architectures and the algorithms that make fog systems. Challenges and research directions are also introduced. In addition, the lessons learned are reviewed and the prospects are discussed in terms of the key role fog is likely to play in emerging technologies such as tactile Internet

Fog computing for sustainable smart cities: a survey

The Internet of Things (IoT) aims to connect billions of smart objects to the Internet, which can bring a promising future to smart cities. These objects are expected to generate large amounts of data and send the data to the cloud for further processing, specially for knowledge discovery, in order that appropriate actions can be taken. However, in reality sensing all possible data items captured by a smart object and then sending the complete captured data to the cloud is less useful. Further, such an approach would also lead to resource wastage (e.g. network, storage, etc.). The Fog (Edge) computing paradigm has been proposed to counterpart the weakness by pushing processes of knowledge discovery using data analytics to the edges. However, edge devices have limited computational capabilities. Due to inherited strengths and weaknesses, neither Cloud computing nor Fog computing paradigm addresses these challenges alone. Therefore, both paradigms need to work together in order to build an sustainable IoT infrastructure for smart cities. In this paper, we review existing approaches that have been proposed to tackle the challenges in the Fog computing domain. Specifically, we describe several inspiring use case scenarios of Fog computing, identify ten key characteristics and common features of Fog computing, and compare more than 30 existing research efforts in this domain. Based on our review, we further identify several major functionalities that ideal Fog computing platforms should support and a number of open challenges towards implementing them, so as to shed light on future research directions on realizing Fog computing for building sustainable smart cities

Semantics-aware content delivery framework for 3D Tele-immersion

3D Tele-immersion (3DTI) technology allows full-body, multimodal interaction among geographically dispersed users, which opens a variety of possibilities in cyber collaborative applications such as art performance, exergaming, and physical rehabilitation. However, with its great potential, the resource and quality demands of 3DTI rise inevitably, especially when some advanced applications target resource-limited computing environments with stringent scalability demands. Under these circumstances, the tradeoffs between 1) resource requirements, 2) content complexity, and 3) user satisfaction in delivery of 3DTI services are magnified. In this dissertation, we argue that these tradeoffs of 3DTI systems are actually avoidable when the underlying delivery framework of 3DTI takes the semantic information into consideration. We introduce the concept of semantic information into 3DTI, which encompasses information about the three factors: environment, activity, and user role in 3DTI applications. With semantic information, 3DTI systems are able to 1) identify the characteristics of its computing environment to allocate computing power and bandwidth to delivery of prioritized contents, 2) pinpoint and discard the dispensable content in activity capturing according to properties of target application, and 3) differentiate contents by their contributions on fulfilling the objectives and expectation of user’s role in the application so that the adaptation module can allocate resource budget accordingly. With these capabilities we can change the tradeoffs into synergy between resource requirements, content complexity, and user satisfaction. We implement semantics-aware 3DTI systems to verify the performance gain on the three phases in 3DTI systems’ delivery chain: capturing phase, dissemination phase, and receiving phase. By introducing semantics information to distinct 3DTI systems, the efficiency improvements brought by our semantics-aware content delivery framework are validated under different application requirements, different scalability bottlenecks, and different user and application models. To sum up, in this dissertation we aim to change the tradeoff between requirements, complexity, and satisfaction in 3DTI services by exploiting the semantic information about the computing environment, the activity, and the user role upon the underlying delivery systems of 3DTI. The devised mechanisms will enhance the efficiency of 3DTI systems targeting on serving different purposes and 3DTI applications with different computation and scalability requirements

The Cloud-to-Thing Continuum

The Internet of Things offers massive societal and economic opportunities while at the same time significant challenges, not least the delivery and management of the technical infrastructure underpinning it, the deluge of data generated from it, ensuring privacy and security, and capturing value from it. This Open Access Pivot explores these challenges, presenting the state of the art and future directions for research but also frameworks for making sense of this complex area. This book provides a variety of perspectives on how technology innovations such as fog, edge and dew computing, 5G networks, and distributed intelligence are making us rethink conventional cloud computing to support the Internet of Things. Much of this book focuses on technical aspects of the Internet of Things, however, clear methodologies for mapping the business value of the Internet of Things are still missing. We provide a value mapping framework for the Internet of Things to address this gap. While there is much hype about the Internet of Things, we have yet to reach the tipping point. As such, this book provides a timely entrée for higher education educators, researchers and students, industry and policy makers on the technologies that promise to reshape how society interacts and operates